/**
 * This program is free software, you can redistribute it and/or modify it.
 * Copyright (c) 2025 Huawei Technologies Co., Ltd.
 * This file is a part of the CANN Open Software.
 * Licensed under CANN Open Software License Agreement Version 2.0 (the "License").
 * Please refer to the License for details. You may not use this file except in compliance with the License.
 * THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING
 * BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
 * See LICENSE in the root of the software repository for the full text of the License.
 */

#include <iostream>
#include <vector>
#include "acl/acl.h"
#include "aclnnop/aclnn_transform_bias_rescale_qkv.h"

#define CHECK_RET(cond, return_expr) \
    do {                             \
        if (!(cond)) {               \
            return_expr;             \
        }                            \
    } while (0)

#define LOG_PRINT(message, ...)         \
    do {                                \
        printf(message, ##__VA_ARGS__); \
    } while (0)

int64_t GetShapeSize(const std::vector<int64_t>& shape)
{
    int64_t shapeSize = 1;
    for (auto i : shape) {
        shapeSize *= i;
    }
    return shapeSize;
}

void PrintOutResult(std::vector<int64_t>& shape, void** deviceAddr)
{
    auto size = GetShapeSize(shape);
    std::vector<float> resultData(size, 0);
    auto ret = aclrtMemcpy(
        resultData.data(), resultData.size() * sizeof(resultData[0]), *deviceAddr, size * sizeof(resultData[0]),
        ACL_MEMCPY_DEVICE_TO_HOST);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("copy result from device to host failed. ERROR: %d\n", ret); return);
    for (int64_t i = 0; i < size; i++) {
        LOG_PRINT("outPut result[%ld] is: %f\n", i, resultData[i]);
    }
}

void PrintInResult(std::vector<int64_t>& shape, void** deviceAddr)
{
    auto size = GetShapeSize(shape);
    std::vector<float> resultData(size, 0);
    auto ret = aclrtMemcpy(
        resultData.data(), resultData.size() * sizeof(resultData[0]), *deviceAddr, size * sizeof(resultData[0]),
        ACL_MEMCPY_DEVICE_TO_HOST);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("copy result from device to host failed. ERROR: %d\n", ret); return);
    for (int64_t i = 0; i < size; i++) {
        LOG_PRINT("input[%ld] is: %f\n", i, resultData[i]);
    }
}

int Init(int32_t deviceId, aclrtStream* stream)
{
    // (Fixed writing) Initialize.
    auto ret = aclInit(nullptr);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclInit failed. ERROR: %d\n", ret); return ret);
    ret = aclrtSetDevice(deviceId);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtSetDevice failed. ERROR: %d\n", ret); return ret);
    ret = aclrtCreateStream(stream);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtCreateStream failed. ERROR: %d\n", ret); return ret);
    return 0;
}

template <typename T>
int CreateAclTensor(
    const std::vector<T>& hostData, const std::vector<int64_t>& shape, void** deviceAddr, aclDataType dataType,
    aclTensor** tensor)
{
    auto size = GetShapeSize(shape) * sizeof(T);
    // Call aclrtMalloc to allocate memory on the device.
    auto ret = aclrtMalloc(deviceAddr, size, ACL_MEM_MALLOC_HUGE_FIRST);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtMalloc failed. ERROR: %d\n", ret); return ret);
    // Call aclrtMemcpy to copy the data on the host to the memory on the device.
    ret = aclrtMemcpy(*deviceAddr, size, hostData.data(), size, ACL_MEMCPY_HOST_TO_DEVICE);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtMemcpy failed. ERROR: %d\n", ret); return ret);

    // Compute the strides of the contiguous tensor.
    std::vector<int64_t> strides(shape.size(), 1);
    for (int64_t i = shape.size() - 2; i >= 0; i--) {
        strides[i] = shape[i + 1] * strides[i + 1];
    }

    // Call aclCreateTensor to create an aclTensor.
    *tensor = aclCreateTensor(
        shape.data(), shape.size(), dataType, strides.data(), 0, aclFormat::ACL_FORMAT_ND, shape.data(), shape.size(),
        *deviceAddr);
    return 0;
}

int main()
{
    // 1. （固定写法）device/stream初始化，参考acl API手册
    // 根据自己的实际device填写deviceId
    int32_t deviceId = 0;
    aclrtStream stream;
    auto ret = Init(deviceId, &stream);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("Init acl failed. ERROR: %d\n", ret); return ret);

    // 2. 构造输入与输出，需要根据API的接口自定义构造
    // qkv
    int64_t B = 3;
    int64_t T = 4;
    int64_t n = 3;
    int64_t d = 16;
    std::vector<int64_t> qkvShape = {B, T, 3 * n * d};
    int qkvCount = B * T * 3 * n * d;
    std::vector<float> qkvHostData(qkvCount, 1);

    for (int i = 0; i < qkvCount; ++i) {
        qkvHostData[i] = i * 1.0;
    }

    void* qkvDeviceAddr = nullptr;
    aclTensor* qkv = nullptr;
    // 创建input aclTensor
    ret = CreateAclTensor(qkvHostData, qkvShape, &qkvDeviceAddr, aclDataType::ACL_FLOAT, &qkv);
    CHECK_RET(ret == ACL_SUCCESS, return ret);

    // qkvBias
    std::vector<int64_t> qkvBiasShape = {3 * n * d};
    std::vector<float> qkvBiasHostData(3 * n * d, 0.5);

    void* qkvBiasDeviceAddr = nullptr;
    aclTensor* qkvBias = nullptr;
    // 创建input aclTensor
    ret = CreateAclTensor(qkvBiasHostData, qkvBiasShape, &qkvBiasDeviceAddr, aclDataType::ACL_FLOAT, &qkvBias);
    CHECK_RET(ret == ACL_SUCCESS, return ret);

    std::vector<int64_t> outShape = {B, n, T, d};
    std::vector<float> outHostData(qkvCount / 3, 1);
    aclTensor* outQ = nullptr;
    aclTensor* outK = nullptr;
    aclTensor* outV = nullptr;
    void* outQDeviceAddr = nullptr;
    void* outKDeviceAddr = nullptr;
    void* outVDeviceAddr = nullptr;

    // 创建out aclTensor
    ret = CreateAclTensor(outHostData, outShape, &outQDeviceAddr, aclDataType::ACL_FLOAT, &outQ);
    ret = CreateAclTensor(outHostData, outShape, &outKDeviceAddr, aclDataType::ACL_FLOAT, &outK);
    ret = CreateAclTensor(outHostData, outShape, &outVDeviceAddr, aclDataType::ACL_FLOAT, &outV);

    CHECK_RET(ret == ACL_SUCCESS, return ret);

    // 3. 调用CANN算子库API，需要修改为具体的Api名称
    uint64_t workspaceSize = 16 * 1024 * 1024;
    aclOpExecutor* executor;

    // LOG_PRINT("qkv input=====");
    // PrintInResult(qkvShape, &qkvDeviceAddr);

    // LOG_PRINT("qkvBias input=====");
    // PrintInResult(qkvBiasShape, &qkvBiasDeviceAddr);

    // 调用aclnnTransformBiasRescaleQkv第一段接口
    ret = aclnnTransformBiasRescaleQkvGetWorkspaceSize(qkv, qkvBias, n, outQ, outK, outV, &workspaceSize, &executor);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnTransformBiasRescaleQkvGetWorkspaceSize failed. ERROR: %d\n", ret);
              return ret);

    // 根据第一段接口计算出的workspaceSize申请device内存
    void* workspaceAddr = nullptr;
    if (workspaceSize > 0) {
        ret = aclrtMalloc(&workspaceAddr, workspaceSize, ACL_MEM_MALLOC_HUGE_FIRST);
        CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("allocate workspace failed. ERROR: %d\n", ret); return ret);
    }

    // 调用aclnnTransformBiasRescaleQkv第二段接口
    ret = aclnnTransformBiasRescaleQkv(workspaceAddr, workspaceSize, executor, stream);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnTransformBiasRescaleQkv failed. ERROR: %d\n", ret); return ret);

    // 4. （固定写法）同步等待任务执行结束
    ret = aclrtSynchronizeStream(stream);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtSynchronizeStream failed. ERROR: %d\n", ret); return ret);

    // 5. 获取输出的值，将device侧内存上的结果复制至host侧，需要根据具体API的接口定义修改
    LOG_PRINT("q output=====");
    PrintOutResult(outShape, &outQDeviceAddr);

    LOG_PRINT("k output=====");
    PrintOutResult(outShape, &outKDeviceAddr);

    LOG_PRINT("v output=====");
    PrintOutResult(outShape, &outVDeviceAddr);

    // 6. 释放aclTensor和aclTensor，需要根据具体API的接口定义修改
    aclDestroyTensor(qkv);
    aclDestroyTensor(qkvBias);
    aclDestroyTensor(outQ);
    aclDestroyTensor(outK);
    aclDestroyTensor(outV);

    // 7.释放device资源，需要根据具体API的接口定义修改
    aclrtFree(qkvDeviceAddr);
    aclrtFree(qkvBiasDeviceAddr);

    aclrtFree(outQDeviceAddr);
    aclrtFree(outKDeviceAddr);
    aclrtFree(outVDeviceAddr);

    if (workspaceSize > 0) {
        aclrtFree(workspaceAddr);
    }
    aclrtDestroyStream(stream);
    aclrtResetDevice(deviceId);
    aclFinalize();

    return 0;
}